This project implements a fuzzy logic system for making procurement decisions. It takes into account factors such as usage rate, delivery time, supplier reliability, and budget to determine the priority level for procurement actions. The system is built using Python and utilizes the scikit-fuzzy library for fuzzy logic operations.
The project consists of the following components:
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Definition of Antecedents: Factors influencing procurement decisions like usage rate, delivery time, supplier reliability, and budget are defined with their respective membership functions.
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Definition of Consequent: The procurement action is defined as the output variable with different priority levels such as low, moderate, and high.
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Rule Definition: A set of rules is defined to map the input variables to the output procurement action based on fuzzy logic.
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Simulation: Example input values are provided, and the system simulates the procurement action based on these inputs.
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Visualization: Membership functions and aggregated results are visualized to understand the decision-making process.
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Decision Making: Finally, a decision is made based on the defuzzified result, determining whether to place an order or not.
This project can serve as a practical implementation of fuzzy logic in decision-making scenarios, particularly in procurement or supply chain management contexts.